A type of displays often used for presenting video signals (such as television) are known as (sample and) hold type displays. An example of a hold time display is Liquid Crystal Displays (LCDs) which are used in many current televisions. For most LCD television and displays, hold times are typically 20 msec.
In contrast to conventional Cathode Ray Tube (CRT) displays wherein an electron beam sweeps the surface of a cathode ray tube to light any given part of the screen only for a miniscule fraction of the frame time, the image of a hold type display is sampled and held constant for the entire frame time. The hold effect corresponds to a time domain filtering by a finite impulse response filter having a square impulse response with a duration equal to the frame time. As this corresponds to a frequency domain low pass filtering (with a sin x/x pulse shape), the sample and hold approach can significantly reduce the temporal bandwidth resulting in significantly reduced dynamic performance and in particular in perceptible motion blur.
Thus, hold-type displays such as LCD displays are characterized by a high spatial bandwidth and low temporal bandwidth. This does not only affect the visibility of image details, but also affects the visibility of noise in video signals in several aspects. Firstly, noise is more visible on such displays (compared to e.g. CRTs) because the high spatial bandwidth means that there is no attenuation of high spatial frequencies by the display. Furthermore, the low temporal bandwidth not only introduces motion blur for moving objects in the image but also results in noise being increasingly perceptible to a user due to the long hold time for the individual frame.
The first aspect is addressed by using efficient noise reduction techniques that can reduce the spatial noise. Such noise reduction techniques typically include elements of spatial low pass filtering to reduce the high spatial bandwidth of the display (while at the same time seeking to maintain the sharpness associated with the high spatial resolution, for example by using edge preserving noise reduction algorithms).
In order to address motion blur, techniques have been introduced which seek to efficiently reduce the hold time for the video signal, corresponding to an increase in temporal bandwidth. Examples of such techniques are presented in “Comparison of LCD Motion Blur Reduction Methods using Temporal Impulse Response and MPRT”, Michiel Klompenhouwer, Proceedings of the SID, 54.1, 2006. Such techniques can be divided in two categories: impulse driving (scanning backlight, black frame insertion, . . . ) and increased frame rate. Since the former will introduce large area flicker if the frame rate is not increased, state of the art motion blur reduction will first increase frame rate, and only then optionally apply impulse driving. Since no input video formats provide increased frame rate, state of the art motion blur reduction includes motion estimation with motion compensated frame rate up-conversion as for example described in “Video Processing for Optimal Motion Portrayal on LCDs”, Frank van Heesch, Michiel Klompenhouwer, et. al, Proceedings of the IDW, 2006. Thus, in such a method, motion estimates are made for moving objects and the estimated motion compensation is introduced to interpolated upconverted frames thereby resulting in an increased frame rate and thus reduced hold time.
However, although such methods may increase the temporal bandwidth of hold-type displays for moving objects, it only reduces the motion blur for the components of the image itself and accordingly only improves the quality of the noise free video signal but does not improve the video noise. In particular, the effect of the hold time on video noise is not reduced. The underlying difference is that the noise free video signal is correlated between frames along the estimated motion direction (and therefore can be motion compensated in the interpolated upconverted frames), while noise is uncorrelated between frames. In other words: the temporal bandwidth of the video signal is increased by these methods, but the temporal bandwidth of the noise is not. This is true for an increased frame rate motion blur reduction system, even when a certain degree of impulse driving is applied. The visible effect of this is a so-called “dirty-window” effect, where the noise seems to be moving differently from the image signal.
Hence, an improved video signal processing would be advantageous and in particular a system allowing increased flexibility, reduced complexity, facilitated implementation, improved temporal performance (in particular for hold time displays), improved perceived video noise reduction, improved video quality and/or improved performance would be advantageous.